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A Master-Slave Game Optimization Model for Electric Power Companies Considering Virtual Power Plant

Authors :
Tao Zhang
Yihong Li
Renwu Yan
Ahmed Abu-Siada
Yuetong Guo
Jing Liu
Ran Huo
Source :
IEEE Access, Vol 10, Pp 21812-21820 (2022)
Publication Year :
2022
Publisher :
IEEE, 2022.

Abstract

As an emerging and active entity in China’s electricity market, electricity selling companies call for a more reliable operational mechanism and new consumption mode to broaden their profit margins. Aiming at distributed power generation-based sales companies and by considering the participation of virtual power plants (VPPs), this paper presents the relevant operating systems in the Chinese power market. Then the paper proposes a new platform for power transactions and optimal dispatch based on a master-slave game optimization model. The model is built so that the main gamer, power sales company, can achieve maximum profit while at the same time the secondary gamer, represented by the VPP attains the lowest internal dispatching cost. The energy of both parties is linked together, and the two parties continuously exchange their own strategies and optimize the operational decisions and scheduling plans iteratively. The results of the investigated case study reveal the benefits to retail electricity companies from adopting the proposed model to aggregate and manage decentralized resources, and optimize decision-making. The platform facilitates the use of controllable loads and distributed energy sources to participate in market transactions on a large scale, and optimize the operational strategies of electric utilities.

Details

Language :
English
ISSN :
21693536
Volume :
10
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.fa7272dfe12942ffa945b9f103bf002c
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2022.3152805